For questions about the plugin, open a topic in the Discuss forums. For bugs or feature requests, open an issue in Github.
For the list of Elastic supported plugins, please consult the Elastic Support Matrix.

Author: Rodrigo De Castro <rdc@google.com>
Date: 2013-09-20
Copyright 2013 Google Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

Summary: plugin to upload log events to Google BigQuery (BQ), rolling
files based on the date pattern provided as a configuration setting. Events
are written to files locally and, once file is closed, this plugin uploads
it to the configured BigQuery dataset.

VERY IMPORTANT:
. To make good use of BigQuery, your log events should be parsed and
structured. Consider using grok to parse your events into fields that can
be uploaded to BQ.
. You must configure your plugin so it gets events with the same structure,
so the BigQuery schema suits them. In case you want to upload log events
with different structures, you can utilize multiple configuration blocks,
separating different log events with Logstash conditionals. More details on
Logstash conditionals can be found here:
http://logstash.net/docs/1.2.1/configuration#conditionals

Experiment with the settings depending on how much log data you generate,
your needs to see "fresh" data, and how much data you could lose in the event
of crash. For instance, if you want to see recent data in BQ quickly, you
could configure the plugin to upload data every minute or so (provided you
have enough log events to justify that). Note also, that if uploads are too
frequent, there is no guarantee that they will be imported in the same order,
so later data may be available before earlier data.

BigQuery charges for storage and for queries, depending on how much data
it reads to perform a query. These are other aspects to consider when
considering the date pattern which will be used to create new tables and also
how to compose the queries when using BQ. For more info on BigQuery Pricing,
please access:
https://developers.google.com/bigquery/pricing

Indicates if BigQuery should allow extra values that are not represented in the table schema.
If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false.

Add a unique ID to the plugin configuration. If no ID is specified, Logstash will generate one.
It is strongly recommended to set this ID in your configuration. This is particularly useful
when you have two or more plugins of the same type. For example, if you have 2 google_bigquery outputs.
Adding a named ID in this case will help in monitoring Logstash when using the monitoring APIs.